Generalized Plan Recognition

By Henry A. Kautz, James F. Allen. 1986

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Citations in the corpus

Explaining Explanations: An Overview of Interpretability of Machine Learning (2018, background): “Some of the key ideas were proposed years ago in plan recognition [78].”
Plan explicability and predictability for robot task planning (2015, background): “There exists a rich literature on plan recognition [14, 3, 20, 16], and many recent works use these techniques in human-aware planning and human-robot teaming [23, 2, 25].”
Programming by Demonstration Using Version Space Algebra (2003, background): “Kautz and Allen (1986) employ a plan library in the form of a hierarchy of plans connected via abstraction and decomposition relationships.”
Focusing Construction and Selection of Abductive Hypotheses (1993, methodology): “Explanation construction methods: In abductive understanding systems, standard theorem-proving chaining techniques are generally the mechanism for generating candidate explanations (e.g., [Hobbs et al., 1990; Kautz and Allen, 1986]).”
Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning (2018, background): “Some of the key ideas were proposed years ago in plan recognition [78].”
COLLAGEN: Applying Collaborative Discourse Theory to Human-Computer Interaction (2001, background): “Plan recognition ( Kautz & Allen 1986 ) is the process of inferring intentions from actions.”
Abduction, experience, and goals: a model of everyday abductive explanation (1995, methodology): “…than re ecting the changing needs for information that motivate explanation (Charniak & Goldman, 1991; Charniak & Shomony, 1994; Hobbs, Stickel, Appelt, & Martin, 1993; Josephson & Josephson, 1994; Kautz & Allen, 1986; Konolige, 1990; Levesque, 1989; O'Rorke, 1994; Poole, 1989; Zadrozny, 1994).”
Probabilistic Plan Recognition Using Off-the-Shelf Classical Planners (2010, methodology): “The plan recognition problem has been addressed using parsing algorithms (Geib and Goldman 2009), Bayesian network inference algorithms (Bui 2003), and specialized procedures (Kautz and Allen 1986; Lesh and Etzioni 1995; Huber, Durfee, and Wellman 1994).”
Concurrent Plan Recognition and Execution for Human-Robot Teams (2014, background): “Many approaches to plan recognition have been proposed, just a few of which are (Kautz and Allen 1986; Bui 2003; Avrahami-Zilberbrand, Kaminka, and Zarosim 2005; Goldman, Geib, and Miller 1999).”
Action understanding as inverse planning. (2009, methodology): “Various forms of the rationality assumption have been used to achieve this in both logical and probabilistic models of action understanding (Kautz & Allen, 1986; Ng & Russell, 2000; Verma et al., 2006).”
Fine-grained activity recognition by aggregating abstract object usage (2005, background): “Early work on plan recognition [11, 23] had the insight that much behavior follows stereotypical patterns, but lacked well-founded and efficient algorithms for learning and inference, and did not ground their theories in directly sensed experience.”
Plan Recognition as Planning (2009, background): “Work in plan recognition, however, has proceeded independently of the work in planning, using mostly handcrafted libraries or algorithms that are not related to planning [Kautz and Allen, 1986; Vilain, 1990; Charniak and Goldman, 1993; Lesh and Etzioni, 1995; Goldman et al., 1999; Avrahami-Zilberbra”
Techniques for Plan Recognition (2001, background): “Kautz and Allen (1986) differentiated between specialization and decomposition recipes, where specialization captured alternative ways of performing a more general action and decomposition speci¢ed the subgoals that comprised an action.”
Automated Planning and Acting (2016, methodology): “The latter rely on the deterministic planning approaches of Kautz and Allen [320], Ramirez and Geffner [505], or the probabilistic approach of Geib and Goldman [218], as well as the parsing techniques of Pynadath and Wellman [499].”
Autonomous agents modelling other agents: A comprehensive survey and open problems (2017, background): “In AI research and computational linguistics, methods for recognising the goals and plans of agents (Schmidt et al., 1978) were applied in automated dialogue systems to understand and disambiguate the intentions of users (Pollack, 1986; Litman and Allen, 1984).”
Learning Motion Patterns of People for Compliant Robot Motion (2005, background): “…1993), office buildings (Horswill 1993; Nourbakhsh, Powers, and Birchfield 1995; Asoh et al. 1997; Simmons et al. 1997; Arras and Vestli 1998), department stores (Endres, Feiten, and Lawitzky 1998; Gross and Boehme 2000), and museums (Burgard et al. 1999; Thrun et al. 2000; Siegwart et al. 2003).”